quantizer.cpp

#include "quantizer.h"
#include <mlx/ops.h>

namespace mlx_transformer {

mlx::core::array Quantizer::dequantize_int4(
    const mlx::core::array& quantized_weights,
    const mlx::core::array& scales,
    const mlx::core::array& zero_points) {
    
    // Implementation of 4-bit dequantization
    // This is a simplified version for phase 1
    auto dequantized = mlx::core::multiply(quantized_weights, scales);
    
    if (zero_points.size() > 0) {
        dequantized = mlx::core::subtract(dequantized, zero_points);
    }
    
    return dequantized;
}

std::tuple<mlx::core::array, mlx::core::array, mlx::core::array> Quantizer::quantize_int4(
    const mlx::core::array& weights,
    bool use_zero_point,
    bool per_channel) {
    
    // Actual implementation would compute optimal scales and zero points
    // This is a placeholder for Phase 1
    auto shape = weights.shape();
    auto dtype = weights.dtype();
    
    // Create dummy scales (1.0) and zero_points (0.0) for now
    mlx::core::array scales;
    mlx::core::array zero_points;
    mlx::core::array quantized_weights = weights;
    
    if (per_channel) {
        auto num_channels = shape[shape.size() - 1];
        scales = mlx::core::ones({num_channels}, dtype);
        if (use_zero_point) {
            zero_points = mlx::core::zeros({num_channels}, dtype);
        }
    } else {
        scales = mlx::core::ones({1}, dtype);
        if (use_zero_point) {
            zero_points = mlx::core::zeros({1}, dtype);
        }
    }
    
    return {quantized_weights, scales, zero_points};
}

} // namespace mlx_transformer